WebbMason Analytics is a certified Amazon Web Services (AWS) Advanced Consulting Partner and a member of the Amazon Partner Network (APN).
Our team has built AWS-anchored data and analytics platforms in retail, health care, transportation and other business sectors to help transition legacy enterprises from traditional business practices to making decisions based on hard data and insights generated by advanced analytics.
Why we use AWS for data analytics
We have been implementing AWS as the foundational technology for data and analytics platforms since 2010.
Amazon’s secure cloud platform comprises an abundance of services that range from computing power and data storage to developer tools and application deployment. Used together, they form the bedrock of many of the data and analytics platforms we build for
our clients here at WebbMason Analytics.
Using AWS has many benefits for analytics groups where the server demand is constantly changing. In the initial phases, data engineering activities may require storage or compute-optimized servers. At later phases, data science and machine learning require memory- optimized servers. These frequent demand fluctuations are difficult to manage with a static analytics platform.
To manage them, we leverage elastic and serverless technologies, such as Athena, Lambda, EMR and Kinesis. This often translates into significant performance improvements, cost savings, and user satisfaction when compared to traditional solutions.
APN is a global partner network that brings together professional services firms that have demonstrated a deep level of expertise on the AWS platform.
The advanced consulting status is reserved for companies that have proven their ability to design, architect, build, migrate and manage their workloads and applications on AWS.
What our clients can expect
AWS provides the flexibility and scalability our clients need to take an agile, iterative approach to develop, activate and adopt analytic solutions. Using AWS as the foundation of the analytics platform, we can start small, prove the value of data-driven insights and incrementally scale up to tackle new and larger business problems.